Past exam of the philosophy of science supplementary subject of the University of Oxford / 2018 / 8

It is plausible that some claims in current science will be revised, and much stronger to say that every successful part of present science is probably false in every relevant respect. The first is compatible with warranted knowledge. The second needs a substantive argument about the particular claims, their evidence and what “false” means for an approximate or idealized model.

Pessimistic induction points to theories once successful and accepted that were later rejected. Larry Laudan uses historical cases to challenge the inference from predictive success to the truth or successful reference of all theoretical commitments.^[ref] The lesson is especially strong against an indiscriminate realism that treats every productive representation as a literal inventory of nature.

But a historical list is not automatically a representative statistical sample. One must ask which successes were substantial, which theoretical components generated them, what survived and whether current evidence is comparable. The eventual rejection of an entire ontology does not entail that every measurement, mathematical relation or limited-domain prediction associated with it was worthless. Nor does the chance that at least one claim in a large conjunction is false imply a high error probability for each member separately.

Newtonian mechanics illustrates a useful distinction. It is not a universally exact account across all speeds and gravitational regimes, but controlled low-speed and weak-field approximations can remain extremely accurate. That is an empirical and mathematical claim about a domain, not permission to call any false account approximately true. Approximate truth needs interpretable quantities, a specified regime and some account of relevant error. Structural realism similarly needs preserved physical relations rather than merely a shared abstract notation.

The possibility of error therefore matters. It should discipline extrapolation, encourage independent testing and prevent practical success from being turned into unconditional metaphysical certainty. It does not require abandoning the best-supported models within tested domains. An empiricist can retain justified confidence in empirical adequacy, while a selective scientific realist may defend stronger commitments where evidence and intervention support them. Both positions must distinguish fallible confidence from certainty and carefully bounded reliability from unrestricted literal truth.